(
self,
model: torch.nn.Module,
train_data: DataLoader,
optimizer: torch.optim.Optimizer,
gpu_id: int,
save_every: int,
)
| 23 | |
| 24 | class Trainer: |
| 25 | def __init__( |
| 26 | self, |
| 27 | model: torch.nn.Module, |
| 28 | train_data: DataLoader, |
| 29 | optimizer: torch.optim.Optimizer, |
| 30 | gpu_id: int, |
| 31 | save_every: int, |
| 32 | ) -> None: |
| 33 | self.gpu_id = gpu_id |
| 34 | self.model = model.to(gpu_id) |
| 35 | self.train_data = train_data |
| 36 | self.optimizer = optimizer |
| 37 | self.save_every = save_every |
| 38 | self.model = DDP(model, device_ids=[gpu_id]) |
| 39 | |
| 40 | def _run_batch(self, source, targets): |
| 41 | self.optimizer.zero_grad() |
nothing calls this directly
no outgoing calls
no test coverage detected